Comprehensive Course List Across 8 Semesters
| Semester | Course Code | Full Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | MTH101 | Mathematics I | 3-1-0-4 | - |
| 1 | PHY101 | Physics I | 3-1-0-4 | - |
| 1 | CHE101 | Chemistry I | 3-1-0-4 | - |
| 1 | EG101 | Engineering Graphics | 2-0-2-3 | - |
| 1 | CP101 | Computer Programming | 3-0-2-4 | - |
| 1 | ENG101 | English for Engineers | 2-0-0-2 | - |
| 1 | LAB101 | Mathematics Lab I | 0-0-2-1 | MTH101 |
| 1 | LAB102 | Physics Lab I | 0-0-2-1 | PHY101 |
| 1 | LAB103 | Chemistry Lab I | 0-0-2-1 | CHE101 |
| 1 | LAB104 | Computer Programming Lab | 0-0-2-1 | CP101 |
| 2 | MTH102 | Mathematics II | 3-1-0-4 | MTH101 |
| 2 | PHY102 | Physics II | 3-1-0-4 | PHY101 |
| 2 | CHE102 | Chemistry II | 3-1-0-4 | CHE101 |
| 2 | EC101 | Electrical Engineering Fundamentals | 3-1-0-4 | - |
| 2 | ME101 | Mechanics of Materials | 3-1-0-4 | - |
| 2 | CP102 | Data Structures and Algorithms | 3-0-2-4 | CP101 |
| 2 | LAB105 | Mathematics Lab II | 0-0-2-1 | MTH102 |
| 2 | LAB106 | Physics Lab II | 0-0-2-1 | PHY102 |
| 2 | LAB107 | Chemistry Lab II | 0-0-2-1 | CHE102 |
| 2 | LAB108 | Computer Programming Lab II | 0-0-2-1 | CP102 |
| 3 | MTH201 | Mathematics III | 3-1-0-4 | MTH102 |
| 3 | PHY201 | Electromagnetic Fields and Waves | 3-1-0-4 | PHY102 |
| 3 | CHE201 | Organic Chemistry | 3-1-0-4 | CHE102 |
| 3 | EC201 | Electronic Devices and Circuits | 3-1-0-4 | EC101 |
| 3 | ME201 | Thermodynamics | 3-1-0-4 | ME101 |
| 3 | CP201 | Database Management Systems | 3-0-2-4 | CP102 |
| 3 | LAB201 | Mathematics Lab III | 0-0-2-1 | MTH201 |
| 3 | LAB202 | Physics Lab III | 0-0-2-1 | PHY201 |
| 3 | LAB203 | Chemistry Lab III | 0-0-2-1 | CHE201 |
| 3 | LAB204 | Electronic Circuits Lab | 0-0-2-1 | EC201 |
| 4 | MTH202 | Mathematics IV | 3-1-0-4 | MTH201 |
| 4 | PHY202 | Optics and Lasers | 3-1-0-4 | PHY201 |
| 4 | CHE202 | Inorganic Chemistry | 3-1-0-4 | CHE201 |
| 4 | EC202 | Signals and Systems | 3-1-0-4 | EC201 |
| 4 | ME202 | Fluid Mechanics | 3-1-0-4 | ME201 |
| 4 | CP202 | Operating Systems | 3-0-2-4 | CP201 |
| 4 | LAB205 | Mathematics Lab IV | 0-0-2-1 | MTH202 |
| 4 | LAB206 | Physics Lab IV | 0-0-2-1 | PHY202 |
| 4 | LAB207 | Chemistry Lab IV | 0-0-2-1 | CHE202 |
| 4 | LAB208 | Operating Systems Lab | 0-0-2-1 | CP202 |
| 5 | MTH301 | Applied Mathematics I | 3-1-0-4 | MTH202 |
| 5 | EC301 | Digital Electronics | 3-1-0-4 | EC202 |
| 5 | ME301 | Mechanics of Machines | 3-1-0-4 | ME202 |
| 5 | CP301 | Computer Networks | 3-0-2-4 | CP202 |
| 5 | CH301 | Environmental Chemistry | 3-1-0-4 | CHE202 |
| 5 | EE301 | Power Electronics | 3-1-0-4 | EC301 |
| 5 | LAB301 | Applied Mathematics Lab I | 0-0-2-1 | MTH301 |
| 5 | LAB302 | Digital Electronics Lab | 0-0-2-1 | EC301 |
| 5 | LAB303 | Mechanics of Machines Lab | 0-0-2-1 | ME301 |
| 5 | LAB304 | Computer Networks Lab | 0-0-2-1 | CP301 |
| 6 | MTH302 | Applied Mathematics II | 3-1-0-4 | MTH301 |
| 6 | EC302 | Microprocessor and Microcontroller | 3-1-0-4 | EC301 |
| 6 | ME302 | Design of Machine Elements | 3-1-0-4 | ME301 |
| 6 | CP302 | Software Engineering | 3-0-2-4 | CP301 |
| 6 | CH302 | Biochemistry | 3-1-0-4 | CH301 |
| 6 | EE302 | Control Systems | 3-1-0-4 | EE301 |
| 6 | LAB305 | Applied Mathematics Lab II | 0-0-2-1 | MTH302 |
| 6 | LAB306 | Microprocessor Lab | 0-0-2-1 | EC302 |
| 6 | LAB307 | Design of Machine Elements Lab | 0-0-2-1 | ME302 |
| 6 | LAB308 | Software Engineering Lab | 0-0-2-1 | CP302 |
| 7 | MTH401 | Advanced Mathematics I | 3-1-0-4 | MTH302 |
| 7 | EC401 | Antennas and Wave Propagation | 3-1-0-4 | EC302 |
| 7 | ME401 | Manufacturing Processes | 3-1-0-4 | ME302 |
| 7 | CP401 | Artificial Intelligence and Machine Learning | 3-0-2-4 | CP302 |
| 7 | CH401 | Industrial Chemistry | 3-1-0-4 | CH302 |
| 7 | EE401 | Electrical Machines | 3-1-0-4 | EE302 |
| 7 | LAB401 | Advanced Mathematics Lab I | 0-0-2-1 | MTH401 |
| 7 | LAB402 | Antennas and Wave Propagation Lab | 0-0-2-1 | EC401 |
| 7 | LAB403 | Manufacturing Processes Lab | 0-0-2-1 | ME401 |
| 7 | LAB404 | AI/ML Lab | 0-0-2-1 | CP401 |
| 8 | MTH402 | Advanced Mathematics II | 3-1-0-4 | MTH401 |
| 8 | EC402 | Embedded Systems | 3-1-0-4 | EC401 |
| 8 | ME402 | Project Management | 3-1-0-4 | ME401 |
| 8 | CP402 | Cloud Computing | 3-0-2-4 | CP401 |
| 8 | CH402 | Pharmaceutical Chemistry | 3-1-0-4 | CH401 |
| 8 | EE402 | Power Systems | 3-1-0-4 | EE401 |
| 8 | LAB405 | Advanced Mathematics Lab II | 0-0-2-1 | MTH402 |
| 8 | LAB406 | Embedded Systems Lab | 0-0-2-1 | EC402 |
| 8 | LAB407 | Project Management Lab | 0-0-2-1 | ME402 |
| 8 | LAB408 | Cloud Computing Lab | 0-0-2-1 | CP402 |
Detailed Departmental Elective Courses
Advanced departmental electives provide students with specialized knowledge and skills in emerging areas of engineering. These courses are designed to align with industry trends and prepare students for future challenges.
The Artificial Intelligence and Machine Learning course introduces students to fundamental concepts of AI, including neural networks, deep learning, reinforcement learning, natural language processing, and computer vision. Students will work on real-world projects such as building recommendation systems, image classification models, and chatbots. The course emphasizes both theoretical understanding and practical implementation using popular frameworks like TensorFlow, PyTorch, and Scikit-learn.
The Internet of Things (IoT) course covers the architecture, protocols, sensors, actuators, and communication technologies used in IoT applications. Students will design and implement IoT systems for smart homes, agriculture monitoring, healthcare tracking, and industrial automation. The course includes hands-on labs using Raspberry Pi, Arduino, and cloud platforms like AWS IoT Core and Google Cloud IoT.
The Cybersecurity course focuses on protecting digital assets from threats and attacks. It covers network security, cryptography, secure programming practices, penetration testing, and incident response. Students will learn to develop secure applications, conduct vulnerability assessments, and understand compliance frameworks such as ISO 27001 and NIST Cybersecurity Framework.
The Data Analytics course teaches students how to extract insights from large datasets using statistical methods, data visualization tools, and machine learning algorithms. Topics include regression analysis, clustering, time series forecasting, and big data technologies like Hadoop and Spark. Students will work on projects involving predictive modeling for financial markets, customer behavior analysis, and healthcare data interpretation.
The Renewable Energy Systems course explores the principles and applications of solar, wind, hydroelectric, geothermal, and biomass energy systems. Students will study power generation technologies, energy storage solutions, smart grid integration, and environmental impact assessments. The course includes lab sessions on designing photovoltaic panels, analyzing wind turbines, and simulating renewable energy systems using MATLAB/Simulink.
The Biomedical Engineering course integrates engineering principles with medical sciences to solve healthcare problems. Students will learn about biomaterials, biomechanics, medical imaging, bioinstrumentation, and tissue engineering. The course includes laboratory sessions on designing prosthetic limbs, developing wearable health monitors, and creating diagnostic tools for early disease detection.
The Automotive Engineering course covers vehicle dynamics, engine design, electric vehicles, autonomous driving systems, and automotive safety standards. Students will study propulsion systems, chassis design, aerodynamics, and control systems. The course includes hands-on labs on engine testing, vehicle simulation, and autonomous navigation using sensors and AI algorithms.
The Robotics and Automation course introduces students to robotics fundamentals, kinematics, control systems, sensor integration, and human-robot interaction. Students will design and build robots for various tasks such as manipulation, navigation, and collaborative work. The course includes programming exercises using ROS (Robot Operating System) and simulation tools like Gazebo.
The Smart Grid Technologies course focuses on modern power grid systems that integrate renewable energy sources, smart meters, demand response programs, and energy storage technologies. Students will learn about grid stability, load forecasting, voltage regulation, and cybersecurity in power systems. The course includes simulations using PowerWorld Simulator and MATLAB.
The Sustainable Construction course addresses green building practices, sustainable materials, energy-efficient design, and environmental impact assessment. Students will study LEED certification, life cycle analysis, carbon footprint reduction, and urban planning strategies. The course includes case studies of sustainable buildings worldwide and field visits to green construction sites.
Project-Based Learning Philosophy
The department emphasizes a project-based learning approach that encourages students to apply theoretical knowledge in real-world scenarios. This methodology fosters innovation, teamwork, and critical thinking while building technical competencies.
Mini-projects are introduced from the second year onwards, allowing students to explore specific areas of interest under faculty guidance. These projects typically last 6-8 weeks and require students to define objectives, conduct research, design solutions, and present findings. Evaluation criteria include project documentation, oral presentation skills, innovation, and teamwork.
The final-year thesis/capstone project is a comprehensive endeavor that spans the entire academic year. Students select a topic aligned with their specialization and work closely with a faculty mentor to develop a significant engineering solution or research study. The project must demonstrate mastery of core concepts, originality, and practical relevance.
Project selection is based on student interests, availability of resources, and alignment with industry needs. Faculty mentors are assigned according to expertise areas and project requirements. Students may collaborate with industry partners or participate in university-sponsored initiatives to enhance the impact of their work.
Evaluation of projects involves multiple stages including proposal review, progress updates, mid-term presentations, and final submissions. Peer evaluations, faculty feedback, and external reviewers contribute to a holistic assessment process. Successful projects are showcased at annual innovation exhibitions and may lead to patent applications or startup ventures.